阅读说明：本技术 一种基于星载关联性健康基线卫星在轨实时监测方法 (Satellite on-orbit real-time monitoring method based on satellite-borne relevance health baseline ) 是由 陶来发 宋登巍 王超 程玉杰 吕琛 于 2020-12-03 设计创作，主要内容包括：本申请提出一种基于星载关联性健康基线卫星在轨实时监测方法,其包括：第一步,健康基线配置；第二步,数据缓存与计算触发；第三步,工况判断；第四步,基线搜索与调用；第五步,关联性计算；第六步,异常判定。本方法采用基于解析方程的健康基线,实时在轨关联性监测,凸显其计算资源占用少、计算时间消耗少的优势；采用缓存池定时触发计算的方法,降低了对数据存储的要求,同时提升响应速度。(The application provides an in-orbit real-time monitoring method based on satellite-borne relevance health baseline satellites, which comprises the following steps: a first step, healthy baseline configuration; secondly, data caching and calculation triggering; thirdly, judging the working condition; fourthly, base line searching and calling; fifthly, calculating the relevance; and sixthly, judging the abnormity. The method adopts the health baseline based on the analytic equation, monitors the on-orbit relevance in real time, and highlights the advantages of less occupied computing resources and less consumed computing time; by adopting the method of the cache pool timing trigger calculation, the requirement on data storage is reduced, and meanwhile, the response speed is improved.)

1. An in-orbit real-time monitoring method of a satellite based on satellite-borne relevance health baseline, which comprises the following steps:

a first step, healthy baseline configuration;

secondly, data caching and calculation triggering; receiving and caching on-satellite monitoring parameters in real time, and triggering subsequent calculation when a triggering condition is met;

thirdly, judging the working condition; judging whether the current data segment belongs to the target working condition or not according to the working condition sensitive parameters and the configured working condition judging logic expression, and if so, turning to the subsequent step;

fourthly, base line searching and calling; searching a correlation health baseline meeting the current telemetering parameters and the target working condition in a configured health baseline library, and calling out the correlation health baseline for correlation calculation;

fifthly, calculating the relevance; calculating to obtain a dependent variable telemetry parameter correlation value, a correlation threshold lower limit sequence and a correlation threshold upper limit sequence according to the correlation health baseline configuration;

sixthly, judging the abnormity; and judging the relation between the actual value of the dependent variable telemetering parameter and the lower limit sequence and the upper limit sequence of the associated threshold according to the judgment criterion, and judging whether the associated relation is normal or abnormal.

2. The satellite-borne relevance-based healthy baseline satellite in-orbit real-time monitoring method according to claim 1, wherein:

in the first step, necessary information required for relevance calculation is configured; the configuration items comprise: relevance calculation telemetering parameters, working condition sensitive parameters, working condition discrimination logic expressions, relevance health baseline analytical function models, relevance health baseline threshold values, data cache pool lengths and anomaly judgment rules.

3. The satellite-borne relevance-based healthy baseline satellite in-orbit real-time monitoring method according to claim 2, wherein:

in the second step, a data cache pool is set for each telemetry parameter; when the cache pool is full, all data in the cache pool corresponding to the telemetering parameters participating in relevance calculation are taken out, transmitted to a calculation engine composed of operation rules such as a working condition discrimination logic expression, a relevance health baseline analysis function, a relevance health baseline threshold function and the like, and used for triggering working condition judgment and calling a health baseline to carry out relevance calculation; when the data in the cache pool is taken out, emptying the cache pool, and continuously receiving the subsequent telemetering parameters; the telemetering parameter sequence which is taken out from the data cache pool and participates in relevance calculation at each time is independent telemetering parameters and dependent telemetering parameters; and the working condition sensitive telemetering parameters which are taken out from the data cache pool each time and used for working condition judgment are working condition sensitive telemetering parameters.

4. The satellite-borne relevance-based healthy baseline satellite in-orbit real-time monitoring method according to claim 3, wherein:

in the third step, the working condition sensitive telemetering parameter value corresponding to each time point of the time axis corresponding to each working condition parameter is input into a working condition discrimination logic expression to obtain a Boolean quantity sequence; the point of the Boolean quantity sequence with the median value being true represents that the corresponding moment meets the target working condition, otherwise, the point does not meet the target working condition; if all the flag bits in the Boolean quantity sequence are true, judging that the section of data belongs to a target working condition; otherwise, judging that the section of data does not belong to the target working condition; if the data segment belongs to the target working condition, calling a correlation health baseline analysis function and a correlation health baseline threshold function, and triggering correlation calculation; and if the data segment does not belong to the target working condition, discarding the data segment and not triggering the relevance calculation.

5. The satellite-borne relevance-based healthy baseline satellite in-orbit real-time monitoring method according to claim 4, wherein:

in the fourth step, target relevance health baseline configuration including a relevance health baseline, an upper threshold of the relevance health baseline and a lower threshold of the relevance health baseline is searched according to the judged working condition result and the telemetry parameters participating in calculation, and the telemetry parameters participating in relevance calculation are calculated according to the configuration to complete baseline search and call.

6. The satellite-borne relevance-based healthy baseline satellite in-orbit real-time monitoring method according to claim 5, wherein:

in the fifth step, a dependent variable telemetry parameter correlation value, a correlation threshold lower limit and a correlation threshold upper limit corresponding to each independent variable telemetry parameter value are respectively calculated according to the configured correlation health baseline analytic equation, the correlation health baseline threshold lower limit and the correlation health baseline threshold upper limit; and calculating to obtain a correlation value sequence, a correlation threshold lower limit sequence and a correlation threshold upper limit sequence of the dependent variable telemetry parameters aiming at all the telemetry points.

7. The satellite-borne relevance-based healthy baseline satellite in-orbit real-time monitoring method according to claim 6, wherein:

respectively calculating the relation between the actual value of each dependent variable telemetering parameter and the lower limit and the upper limit of the associated threshold, and calculating to generate an overrun flag bit for each remote measuring point; calculating the flag bit of each remote measuring point to obtain an overrun flag bit sequence of the whole remote measuring parameter sequence; calculating the proportion of the total number of the overrun points of the whole sequence to the total length of the sequence; comparing the proportion of the total number of the overrun points of the whole sequence in the total length of the sequence with an overrun proportion judgment threshold value determined in the configuration; if the ratio is larger than the threshold value, judging that the result is abnormal; if the ratio is less than or equal to the threshold, the result is determined to be normal.

Technical Field

The application relates to a satellite health monitoring technology, in particular to an in-orbit real-time satellite monitoring method based on satellite-borne relevance health baseline.

Background

The satellite key subsystem has a plurality of single machine parameters, and the complexity of telemetering data is increased due to the change of the space environment and the replacement of the working condition of the satellite, so that the accurate learning of the real health state of the satellite key subsystem in the in-orbit operation becomes extremely difficult. On one hand, the existing health state judgment technology of the key subsystem is only used for receiving simple telemetering data, analyzing all telemetering data and then manually monitoring and resolving whether the analyzed telemetering data is normal or not in real time, so that the efficiency is low and the human error factor is large; on the other hand, the existing technical means can use only a small amount of historical data, and the abnormality is presumed by manually and simply judging parameters, so that the accuracy is low; meanwhile, the existing technology has less functions of early warning and the like on abnormal states.

Based on the background, the satellite real-time state monitoring is performed from the perspective of parameter correlation. Normally, there is a certain correlation between the values of different telemetry parameters due to structural, functional coupling and influence. When the satellite is in a normal (or healthy) state, the association should remain relatively stable theoretically, and fluctuate randomly within a small range under the influence of operating conditions, environmental interference and data transmission. The satellite relevance state monitoring is that an expected threshold interval of the dependent variable remote parameter is obtained through calculation by starting from the independent variable remote parameter and combining the configuration input relevance coefficient and the threshold coefficient, and then the actual value of the dependent variable remote parameter is compared with the threshold value, so that the satellite relevance state monitoring is realized.

Disclosure of Invention

In view of the above problems, the present application aims to provide an in-orbit real-time satellite monitoring method based on satellite-borne correlation health baseline.

The satellite on-orbit real-time monitoring method based on the satellite-borne relevance health baseline satellite comprises the following steps:

a first step, healthy baseline configuration;

secondly, data caching and calculation triggering; receiving and caching on-satellite monitoring parameters in real time, and triggering subsequent calculation when a triggering condition is met;

thirdly, judging the working condition; judging whether the current data segment belongs to the target working condition or not according to the working condition sensitive parameters and the configured working condition judging logic expression, and if so, turning to the subsequent step;

fourthly, base line searching and calling; searching a correlation health baseline meeting the current telemetering parameters and the target working condition in a configured health baseline library, and calling out the correlation health baseline for correlation calculation;

fifthly, calculating the relevance; calculating to obtain a dependent variable telemetry parameter correlation value, a correlation threshold lower limit sequence and a correlation threshold upper limit sequence according to the correlation health baseline configuration;

sixthly, judging the abnormity; and judging the relation between the actual value of the dependent variable telemetering parameter and the lower limit sequence and the upper limit sequence of the associated threshold according to the judgment criterion, and judging whether the associated relation is normal or abnormal.

Preferably, in the first step, necessary information required for the relevance calculation is configured; the configuration items comprise: relevance calculation telemetering parameters, working condition sensitive parameters, working condition discrimination logic expressions, relevance health baseline analytical function models, relevance health baseline threshold values, data cache pool lengths and anomaly judgment rules.

Preferably, in the second step, a data cache pool is set for each telemetry parameter; when the cache pool is full, all data in the cache pool corresponding to the telemetering parameters participating in relevance calculation are taken out, transmitted to a calculation engine composed of operation rules such as a working condition discrimination logic expression, a relevance health baseline analysis function, a relevance health baseline threshold function and the like, and used for triggering working condition judgment and calling a health baseline to carry out relevance calculation; when the data in the cache pool is taken out, emptying the cache pool, and continuously receiving the subsequent telemetering parameters; the telemetering parameter sequence which is taken out from the data cache pool and participates in relevance calculation at each time is independent telemetering parameters and dependent telemetering parameters; and the working condition sensitive telemetering parameters which are taken out from the data cache pool each time and used for working condition judgment are working condition sensitive telemetering parameters.

Preferably, in the third step, the working condition sensitive telemetry parameter value corresponding to each time point of the time axis corresponding to each working condition parameter is input into the working condition discrimination logic expression to obtain a boolean quantity sequence; the point of the Boolean quantity sequence with the median value being true represents that the corresponding moment meets the target working condition, otherwise, the point does not meet the target working condition; if all the flag bits in the Boolean quantity sequence are true, judging that the section of data belongs to a target working condition; otherwise, judging that the section of data does not belong to the target working condition; if the data segment belongs to the target working condition, calling a correlation health baseline analysis function and a correlation health baseline threshold function, and triggering correlation calculation; and if the data segment does not belong to the target working condition, discarding the data segment and not triggering the relevance calculation.

Preferably, in the fourth step, according to the determined working condition result and the telemetry parameters involved in the calculation, the target correlation health baseline configuration including the correlation health baseline, the upper threshold of the correlation health baseline, and the lower threshold of the correlation health baseline is searched, and the telemetry parameters involved in the correlation calculation are calculated according to the configuration, so that the baseline search and calling are completed.

Preferably, in the fifth step, a dependent variable telemetry parameter correlation value, a correlation threshold lower limit and a correlation threshold upper limit corresponding to each independent variable telemetry parameter value are respectively calculated according to the configured correlation health baseline analytic equation, the correlation health baseline threshold lower limit and the correlation health baseline threshold upper limit; and calculating to obtain a correlation value sequence, a correlation threshold lower limit sequence and a correlation threshold upper limit sequence of the dependent variable telemetry parameters aiming at all the telemetry points.

Preferably, the relation between the actual value of each dependent variable telemetering parameter and the lower limit and the upper limit of the associated threshold is calculated respectively, and an overrun zone bit is calculated and generated for each remote measuring point; calculating the flag bit of each remote measuring point to obtain an overrun flag bit sequence of the whole remote measuring parameter sequence; calculating the proportion of the total number of the overrun points of the whole sequence to the total length of the sequence; comparing the proportion of the total number of the overrun points of the whole sequence in the total length of the sequence with an overrun proportion judgment threshold value determined in the configuration; if the ratio is larger than the threshold value, judging that the result is abnormal; if the ratio is less than or equal to the threshold, the result is determined to be normal.

The invention has the advantages and positive effects that:

compared with the traditional single-parameter threshold monitoring method, the monitoring method based on the relevance health baseline simultaneously brings the quantitative correlation among different parameters into the monitoring range, and can systematically monitor the health state of a satellite typical subsystem from the perspective of multiple parameters;

the universal relevance architecture system and the monitoring method have strong expandability;

the method has the advantages of less occupation of computing resources and high response speed, and can detect and alarm satellite abnormal conditions in time at the satellite-borne end.

Drawings

FIG. 1 is a block flow diagram of an in-orbit real-time satellite monitoring method based on satellite-borne correlation health baseline according to the present application;

2-6 are data cache pools for embodiments of the present application when t is 0s, 15s, 30s, 45s, and 60s, respectively;

FIG. 7 is a result of correlation calculations for an embodiment of the present application;

fig. 8 illustrates a state after a data cache pool is emptied according to an embodiment of the present application.

Detailed Description

The method has the advantages that the satellite-borne computing resources are limited, the requirement on response timeliness is high, the health baseline based on the analytic equation is adopted for satellite engineering application, real-time on-orbit correlation monitoring is achieved, and the advantages of small computing resource occupation and small computing time consumption are highlighted. By adopting the method of the cache pool timing trigger calculation, the requirement on data storage is reduced, and meanwhile, the response speed is improved.

The satellite-borne relevance based healthy baseline satellite in-orbit real-time monitoring method specifically comprises the following steps.

The method comprises the following steps: healthy baseline configuration

First, necessary information required for the relevance calculation is configured. The configuration items comprise: relevance calculation telemetering parameters, working condition sensitive parameters, working condition discrimination logic expressions, relevance health baseline analytical function models, relevance health baseline threshold values, data cache pool lengths and anomaly judgment rules. The meaning of each configuration item is as follows.

(1) And (3) telemetry parameters: telemetry parameters involved in the correlation status monitoring calculation include independent variable telemetry parameters and dependent variable telemetry parameters.

(2) Working condition sensitive parameters: and the remote measuring parameters are used for judging and identifying the target working condition.

(3) And (3) judging a logic expression by a working condition: and when the working condition distinguishing expression is true, the corresponding telemetering parameter value belongs to the target working condition section, otherwise, the telemetering parameter value does not belong to the target working condition section.

(4) Correlation health baseline analytical function model: the analytical function for representing the mapping relationship between the independent variable telemetry parameter and the dependent variable telemetry parameter in the normal state can be uniformly characterized as y ═ f (x), wherein x represents the independent variable telemetry parameter value, and y represents the dependent variable telemetry parameter value. In a satellite-borne monitoring scenario, the correlation health baseline analysis model is generally defined as a linear model, which can be expressed as:

and y ═ f (x) ═ a + bx, where a and b are linear function constant terms and first order term coefficients, respectively.

(5) Correlation health baseline threshold: an associated upper bound and an associated lower bound of the associated healthy baseline are defined in a functional manner. Respectively and associated upper and lower limit functions ofAndy＝F(x) In that respect The threshold of the correlation health baseline is specified in this way, which can represent a threshold setting mode that the calculated value of the correlation health baseline fluctuates up and down by a certain constant, and can also flexibly represent other threshold setting modes.

(6) Length of data buffer pool: and defining the maximum number of the telemetry parameter data points which can be contained in the cache by taking the data points as units. And the telemetering parameter data point at each sampling moment occupies one position, and correlation calculation is triggered when the data cache pool is full.

(7) An abnormality determination rule: and (4) judging the out-of-limit ratio threshold t.

Meanwhile, a baseline updating instruction can be sent at any time on the ground, and after the configuration stage is finished, if the baseline updating instruction sent by the ground is detected, the configuration of the associated healthy baseline is updated according to related parameters in the instruction data packet. The configuration items are as above.

Step two: data caching and computation triggering

A data buffer pool of length n is set for each telemetry parameter. At the satellite-borne end, telemetry data arrives at a data cache area at a certain frequency, and when the cache area is not full, each arriving telemetry data point occupies one position in a cache pool. And when the cache pool is full, taking out all data in the cache pool corresponding to the telemetering parameters participating in relevance calculation, triggering working condition judgment and calling a healthy baseline, and carrying out relevance calculation. And when the data in the cache pool is taken out, clearing the cache pool and continuously receiving the subsequent telemetering parameters. The telemetry parameter sequence which is taken out from the data cache pool once and participates in the relevance calculation is recorded as X ═ X (X)₁,x₂,L,x_n) And Y ═ Y₁,y₂,L,y_n). Wherein X is independent variable remote measuring parameter, Y is dependent variable remote measuring parameter. Recording the working condition sensitive telemetering parameters which are taken out from the data cache pool once and used for working condition judgment as

And c telemetry parameters are contained for judging the working condition.

Step three: condition determination

The judgment logic expression of register condition is Cond (W)₁,W₂,L,W_c) The c working condition sensitive parameters are used as input, and the output value is Boolean true or false.

A time axis T corresponding to the n working condition parameters_c＝(t₁,t₂,L,t_n) Inputting the working condition sensitive telemetering parameter value corresponding to each time point into a working condition discrimination logic expression to obtain a Boolean quantity sequence with the length of n; the point in the sequence with the median being true represents that the corresponding moment meets the target working condition, otherwise, the point does not meet the target working condition. The Boolean sequence is expressed as B ═ f₁,f₂,L,f_n). If all the flag bits in the Boolean quantity sequence are true, judging that the section of data belongs to a target working condition; otherwise, judging that the section of data does not belong to the target working condition. If the data segment belongs to the target working condition, calling a correlation health baseline analysis function and a correlation health baseline threshold function, and triggering correlation calculation; and if the data segment does not belong to the target working condition, discarding the data segment and not triggering the relevance calculation.

Step four: baseline search and invocation

And searching target relevance health baseline configuration comprising a relevance health baseline, an upper threshold value of the relevance health baseline and a lower threshold value of the relevance health baseline according to the judged working condition result and the telemetry parameters participating in the calculation, calculating the telemetry parameters participating in the relevance calculation according to the configuration, and completing the search and the call of the baseline.

Step five: relevance computation

The two telemetering parameter sequences participating in the relevance monitoring calculation are respectively X ═ X (X)₁,x₂,L,x_n) And Y ═ Y₁,y₂,L,y_n). According to the configured correlation health baseline analytical equation y ═ F (x), the lower threshold of the correlation health baseliney＝F(x) And correlation health baseline upper thresholdRespectively calculating the dependent variable telemetering parameter correlation value, the correlation threshold lower limit and the correlation threshold upper limit corresponding to each independent variable telemetering parameter value in the following specific calculation mode

y _i＝F(x_i)

Wherein y _i、Respectively representing values corresponding to independent variable telemetry parameter x_iThe dependent variable telemetry parameter of (1) an associated value, an associated lower threshold, and an associated upper threshold.

The correlation value sequence, the correlation threshold lower limit sequence and the correlation threshold upper limit sequence of the dependent variable telemetry parameters calculated by aiming at all the remote measuring points are as follows

Y＝(y ₁,y ₂,L,y _n)

Step six: abnormality determination

Respectively calculating the relation between the actual value of each dependent variable telemetering parameter and the lower limit and the upper limit of the associated threshold, and calculating to generate an overrun flag epsilon for each telemetering point_iWherein

Calculating the flag bit of each remote measuring point to obtain the over-limit flag bit sequence of the whole remote measuring parameter sequence

E＝(ε₁,ε₂,L,ε_n)

The calculation is carried out in the following way, and whether the segment sequence is abnormal or not is judged:

calculating the total number of overrun points in the whole sequence

Calculating the proportion of the total number of the overrun points of the whole sequence to the total length of the sequence

Where n is the total number of telemetry points participating in the calculation of the telemetry parameter sequence

Comparing the proportion of the total number of the overrun points of the whole sequence in the total length of the sequence with an overrun proportion judgment threshold t determined in the configuration: if c is larger than t, judging that the result is abnormal; if c is less than or equal to t, the result is judged to be normal.

Examples

The method comprises the following steps: healthy baseline configuration

First, necessary information required for the relevance calculation is configured. The configuration items comprise: relevance calculation telemetering parameters, working condition sensitive parameters, working condition discrimination logic expressions, relevance health baseline analytical function models, relevance health baseline threshold values, data cache pool lengths and anomaly judgment rules. The meaning of each configuration item is as follows.

(1) And (3) telemetry parameters: independent variable '1-9 voltage of A group storage battery' and dependent variable 'voltage of A group storage battery'

(2) Correlation health baseline analytical function model: an analytical function y ═ f (x) ═ a + bx ═ -1.644+4.132x which characterizes the mapping between the independent and dependent telemetry parameters, where x denotes the independent telemetry parameter and y denotes the dependent telemetry parameter.

(3) Correlation health baseline threshold: an associated upper bound and an associated lower bound of the associated healthy baseline are defined in a functional manner. Respectively and associated upper and lower limit functions ofAndy＝F(x)＝-2.212+4.087x。

(4) length of data buffer pool: the maximum number of telemetry parameter data points that can be held in the cache is defined to be 60 in units of data points. Each telemetry parameter data point occupies one position, and when the data cache pool is full, relevance calculation is triggered.

(5) An abnormality determination rule: the out-of-limit ratio discrimination threshold t is 0.1.

Meanwhile, a baseline updating instruction is sent out on the ground possibly at variable time, and after the configuration stage is finished, if the baseline updating instruction sent out on the ground is detected, the configuration of the associated health baseline is updated according to related parameters in an instruction data packet. The configuration items are as above.

Step two: data caching and computation triggering

A data buffer pool of length 60 is set for each telemetry parameter. At the satellite-borne end, telemetry data arrives at a data cache area at a certain frequency, and when the cache area is not full, each arriving telemetry data point occupies one position in a cache pool. And when the cache pool is full, all data in the cache pool corresponding to the telemetering parameters participating in relevance calculation are taken out, and working condition judgment and relevance calculation are triggered. And when the data in the cache pool is taken out, clearing the cache pool and continuously receiving the subsequent telemetering parameters. The telemetry parameter sequence which is taken out from the data cache pool once and participates in the relevance calculation is recorded as X ═ X (X)₁，x₂，...，x₆₀) And Y ═ Y₁，y₂，...，y₆₀). Wherein X is independent variable remote measuring parameter, Y is dependent variable remote measuring parameter. Recording the working condition sensitive telemetering parameters which are taken out from the data cache pool once and used for working condition judgment as

X＝(X₁，X₂，...，X₆₀)

Y＝(Y₁，Y₂，...，Y₆₀)

The process of caching the telemetering parameters of the voltage of the A group of storage batteries and the voltage of the A group of storage batteries 1-9 is shown as follows:

when t is 0s, the data buffer pool is as shown in fig. 2.

When t is 15s, the data buffer pool is as shown in fig. 3.

When t is 30s, the data buffer pool is as shown in fig. 4.

When t is 45s, the data buffer pool is as shown in fig. 5.

When t is 60s, the data buffer pool is as shown in fig. 6.

Step three: condition determination

Working condition effective time axis T_c＝(t₁,t₂,L,t₆₀) Inputting the working condition sensitive telemetering parameter value corresponding to each time point into a working condition discrimination logic expression to obtain a Boolean quantity sequence with the length of 60, and recording the Boolean quantity sequence as B ═ f₁,f₂,L,f₆₀). And the judgment result is that all the flag bits in the Boolean quantity sequence are true, so that the data of the section is judged to belong to the target working condition, and a correlation health baseline analysis function and a correlation health baseline threshold function are called to trigger correlation calculation.

Step four: baseline search and invocation

Searching target relevance health baseline configuration, namely relevance type health baseline analytical equation according to judged working condition results and telemetering parameters participating in calculation

y＝F(x)＝a+bx＝-1.644+4.132x

Lower threshold of relevance

y＝F(x)＝-2.212+4.087x

Upper threshold of relevance

And sending the data to a relevance calculation engine to complete the search and call of the base line.

Step five: relevance computation

The two telemetering parameter sequences participating in the relevance monitoring calculation are respectively X ═ X (X)₁,x₂,L,x₆₀) And Y ═ Y₁,y₂,L,y₆₀). According to the configured correlation health baseline analytical equation y ═ F (x), the lower threshold of the correlation health baseliney＝F(x) And correlation health baseline upper thresholdRespectively calculate correspondencesThe dependent variable telemetry parameter associated value, the associated lower threshold value and the associated upper threshold value of each independent variable telemetry parameter value are calculated in the following specific manner

y _i＝F(x_i)

Wherein y _i、Each represents a radical corresponding to x_iThe dependent variable telemetry parameter of (1) an associated value, an associated lower threshold, and an associated upper threshold.

The calculation results are shown in fig. 7.

In the upper graph, the lower subgraph is the original telemetering parameter value of the independent variable telemetering parameter 'A group storage battery 1-9 voltage', the upper subgraph is the original telemetering parameter value of the dependent variable telemetering parameter 'A group storage battery voltage', a telemetering parameter correlation value obtained by calculation according to the independent variable telemetering parameter sequence and the correlation health baseline, and a telemetering parameter threshold interval obtained by calculation according to the independent variable telemetering parameter sequence and the correlation threshold upper and lower limits.

Step six: abnormality determination

Calculating the relation between the actual value of the dependent variable telemetering parameter and the lower limit and the upper limit of the associated threshold, and calculating to generate an overrun flag epsilon for each telemetering point_iWherein

Calculating the flag bit of each remote measuring point to obtain the over-limit flag bit sequence of the whole remote measuring parameter sequence

E＝(ε₁，ε₂，…，ε₆₀)＝(0，0，...，0)

The calculation is carried out in the following way, and whether the segment sequence is abnormal or not is judged:

calculating the total number of overrun points in the whole sequence

Calculating the proportion of the total number of the overrun points of the whole sequence to the total length of the sequence

And comparing the overrun proportion judgment threshold t determined in the configuration of the proportion c of the total number of the overrun points of the whole sequence to the total length of the sequence with 0.1, wherein c is less than or equal to t, and judging that the result is normal.

After the above steps are completed, that is, when t is 61s, the data buffer pool is emptied, and telemetry data of the next cycle is received again, as shown in fig. 8.

Unless defined otherwise, all technical and/or scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The materials, methods, and examples set forth in this application are illustrative only and not intended to be limiting.

Although the present invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications, and variations will be apparent to those skilled in the art in light of the teachings of this application and yet remain within the scope of this application.